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Geo Centroid Aggregation
editGeo Centroid Aggregation
editA metric aggregation that computes the weighted centroid from all coordinate values for a Geo-point field.
Example:
PUT /museums { "mappings": { "properties": { "location": { "type": "geo_point" } } } } POST /museums/_bulk?refresh {"index":{"_id":1}} {"location": "52.374081,4.912350", "city": "Amsterdam", "name": "NEMO Science Museum"} {"index":{"_id":2}} {"location": "52.369219,4.901618", "city": "Amsterdam", "name": "Museum Het Rembrandthuis"} {"index":{"_id":3}} {"location": "52.371667,4.914722", "city": "Amsterdam", "name": "Nederlands Scheepvaartmuseum"} {"index":{"_id":4}} {"location": "51.222900,4.405200", "city": "Antwerp", "name": "Letterenhuis"} {"index":{"_id":5}} {"location": "48.861111,2.336389", "city": "Paris", "name": "Musée du Louvre"} {"index":{"_id":6}} {"location": "48.860000,2.327000", "city": "Paris", "name": "Musée d'Orsay"} POST /museums/_search?size=0 { "aggs" : { "centroid" : { "geo_centroid" : { "field" : "location" } } } }
The |
The above aggregation demonstrates how one would compute the centroid of the location field for all documents with a crime type of burglary
The response for the above aggregation:
{ ... "aggregations": { "centroid": { "location": { "lat": 51.00982965203002, "lon": 3.9662131341174245 }, "count": 6 } } }
The geo_centroid
aggregation is more interesting when combined as a sub-aggregation to other bucket aggregations.
Example:
POST /museums/_search?size=0 { "aggs" : { "cities" : { "terms" : { "field" : "city.keyword" }, "aggs" : { "centroid" : { "geo_centroid" : { "field" : "location" } } } } } }
The above example uses geo_centroid
as a sub-aggregation to a
terms bucket aggregation
for finding the central location for museums in each city.
The response for the above aggregation:
{ ... "aggregations": { "cities": { "sum_other_doc_count": 0, "doc_count_error_upper_bound": 0, "buckets": [ { "key": "Amsterdam", "doc_count": 3, "centroid": { "location": { "lat": 52.371655656024814, "lon": 4.909563297405839 }, "count": 3 } }, { "key": "Paris", "doc_count": 2, "centroid": { "location": { "lat": 48.86055548675358, "lon": 2.3316944623366 }, "count": 2 } }, { "key": "Antwerp", "doc_count": 1, "centroid": { "location": { "lat": 51.22289997059852, "lon": 4.40519998781383 }, "count": 1 } } ] } } }
Using geo_centroid
as a sub-aggregation of geohash_grid
The geohash_grid
aggregation places documents, not individual geo-points, into buckets. If a
document’s geo_point
field contains multiple values, the document
could be assigned to multiple buckets, even if one or more of its geo-points are
outside the bucket boundaries.
If a geocentroid
sub-aggregation is also used, each centroid is calculated
using all geo-points in a bucket, including those outside the bucket boundaries.
This can result in centroids outside of bucket boundaries.